Merge remote-tracking branch 'origin/main' into pr-1546

This commit is contained in:
Re-bin
2026-03-06 07:18:06 +00:00
18 changed files with 750 additions and 207 deletions

1
.gitignore vendored
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@@ -1,3 +1,4 @@
.worktrees/
.assets
.env
*.pyc

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@@ -12,11 +12,11 @@
</p>
</div>
🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw)
🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw).
⚡️ Delivers core agent functionality in just **~4,000** lines of code — **99% smaller** than Clawdbot's 430k+ lines.
⚡️ Delivers core agent functionality with **99% fewer lines of code** than OpenClaw.
📏 Real-time line count: **3,935 lines** (run `bash core_agent_lines.sh` to verify anytime)
📏 Real-time line count: run `bash core_agent_lines.sh` to verify anytime.
## 📢 News
@@ -293,12 +293,18 @@ If you prefer to configure manually, add the following to `~/.nanobot/config.jso
"discord": {
"enabled": true,
"token": "YOUR_BOT_TOKEN",
"allowFrom": ["YOUR_USER_ID"]
"allowFrom": ["YOUR_USER_ID"],
"groupPolicy": "mention"
}
}
}
```
> `groupPolicy` controls how the bot responds in group channels:
> - `"mention"` (default) — Only respond when @mentioned
> - `"open"` — Respond to all messages
> DMs always respond when the sender is in `allowFrom`.
**5. Invite the bot**
- OAuth2 → URL Generator
- Scopes: `bot`
@@ -658,6 +664,7 @@ Config file: `~/.nanobot/config.json`
> - **Zhipu Coding Plan**: If you're on Zhipu's coding plan, set `"apiBase": "https://open.bigmodel.cn/api/coding/paas/v4"` in your zhipu provider config.
> - **MiniMax (Mainland China)**: If your API key is from MiniMax's mainland China platform (minimaxi.com), set `"apiBase": "https://api.minimaxi.com/v1"` in your minimax provider config.
> - **VolcEngine Coding Plan**: If you're on VolcEngine's coding plan, set `"apiBase": "https://ark.cn-beijing.volces.com/api/coding/v3"` in your volcengine provider config.
> - **Alibaba Cloud Coding Plan**: If you're on the Alibaba Cloud Coding Plan (BaiLian), set `"apiBase": "https://coding.dashscope.aliyuncs.com/v1"` in your dashscope provider config.
| Provider | Purpose | Get API Key |
|----------|---------|-------------|
@@ -884,6 +891,33 @@ MCP tools are automatically discovered and registered on startup. The LLM can us
| `channels.*.allowFrom` | `[]` (allow all) | Whitelist of user IDs. Empty = allow everyone; non-empty = only listed users can interact. |
## Multiple Instances
Run multiple nanobot instances simultaneously, each with its own workspace and configuration.
```bash
# Instance A - Telegram bot
nanobot gateway -w ~/.nanobot/botA -p 18791
# Instance B - Discord bot
nanobot gateway -w ~/.nanobot/botB -p 18792
# Instance C - Using custom config file
nanobot gateway -w ~/.nanobot/botC -c ~/.nanobot/botC/config.json -p 18793
```
| Option | Short | Description |
|--------|-------|-------------|
| `--workspace` | `-w` | Workspace directory (default: `~/.nanobot/workspace`) |
| `--config` | `-c` | Config file path (default: `~/.nanobot/config.json`) |
| `--port` | `-p` | Gateway port (default: `18790`) |
Each instance has its own:
- Workspace directory (MEMORY.md, HEARTBEAT.md, session files)
- Cron jobs storage (`workspace/cron/jobs.json`)
- Configuration (if using `--config`)
## CLI Reference
| Command | Description |

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@@ -10,6 +10,7 @@ from typing import Any
from nanobot.agent.memory import MemoryStore
from nanobot.agent.skills import SkillsLoader
from nanobot.utils.helpers import detect_image_mime
class ContextBuilder:
@@ -136,10 +137,14 @@ Reply directly with text for conversations. Only use the 'message' tool to send
images = []
for path in media:
p = Path(path)
mime, _ = mimetypes.guess_type(path)
if not p.is_file() or not mime or not mime.startswith("image/"):
if not p.is_file():
continue
b64 = base64.b64encode(p.read_bytes()).decode()
raw = p.read_bytes()
# Detect real MIME type from magic bytes; fallback to filename guess
mime = detect_image_mime(raw) or mimetypes.guess_type(path)[0]
if not mime or not mime.startswith("image/"):
continue
b64 = base64.b64encode(raw).decode()
images.append({"type": "image_url", "image_url": {"url": f"data:{mime};base64,{b64}"}})
if not images:

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@@ -202,9 +202,18 @@ class AgentLoop:
if response.has_tool_calls:
if on_progress:
clean = self._strip_think(response.content)
if clean:
await on_progress(clean)
thoughts = [
self._strip_think(response.content),
response.reasoning_content,
*(
f"Thinking [{b.get('signature', '...')}]:\n{b.get('thought', '...')}"
for b in (response.thinking_blocks or [])
if isinstance(b, dict) and "signature" in b
),
]
combined_thoughts = "\n\n".join(filter(None, thoughts))
if combined_thoughts:
await on_progress(combined_thoughts)
await on_progress(self._tool_hint(response.tool_calls), tool_hint=True)
tool_call_dicts = [

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@@ -128,6 +128,13 @@ class MemoryStore:
# Some providers return arguments as a JSON string instead of dict
if isinstance(args, str):
args = json.loads(args)
# Some providers return arguments as a list (handle edge case)
if isinstance(args, list):
if args and isinstance(args[0], dict):
args = args[0]
else:
logger.warning("Memory consolidation: unexpected arguments as empty or non-dict list")
return False
if not isinstance(args, dict):
logger.warning("Memory consolidation: unexpected arguments type {}", type(args).__name__)
return False

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@@ -58,17 +58,48 @@ async def connect_mcp_servers(
) -> None:
"""Connect to configured MCP servers and register their tools."""
from mcp import ClientSession, StdioServerParameters
from mcp.client.sse import sse_client
from mcp.client.stdio import stdio_client
from mcp.client.streamable_http import streamable_http_client
for name, cfg in mcp_servers.items():
try:
if cfg.command:
transport_type = cfg.type
if not transport_type:
if cfg.command:
transport_type = "stdio"
elif cfg.url:
# Convention: URLs ending with /sse use SSE transport; others use streamableHttp
transport_type = (
"sse" if cfg.url.rstrip("/").endswith("/sse") else "streamableHttp"
)
else:
logger.warning("MCP server '{}': no command or url configured, skipping", name)
continue
if transport_type == "stdio":
params = StdioServerParameters(
command=cfg.command, args=cfg.args, env=cfg.env or None
)
read, write = await stack.enter_async_context(stdio_client(params))
elif cfg.url:
from mcp.client.streamable_http import streamable_http_client
elif transport_type == "sse":
def httpx_client_factory(
headers: dict[str, str] | None = None,
timeout: httpx.Timeout | None = None,
auth: httpx.Auth | None = None,
) -> httpx.AsyncClient:
merged_headers = {**(cfg.headers or {}), **(headers or {})}
return httpx.AsyncClient(
headers=merged_headers or None,
follow_redirects=True,
timeout=timeout,
auth=auth,
)
read, write = await stack.enter_async_context(
sse_client(cfg.url, httpx_client_factory=httpx_client_factory)
)
elif transport_type == "streamableHttp":
# Always provide an explicit httpx client so MCP HTTP transport does not
# inherit httpx's default 5s timeout and preempt the higher-level tool timeout.
http_client = await stack.enter_async_context(
@@ -82,7 +113,7 @@ async def connect_mcp_servers(
streamable_http_client(cfg.url, http_client=http_client)
)
else:
logger.warning("MCP server '{}': no command or url configured, skipping", name)
logger.warning("MCP server '{}': unknown transport type '{}'", name, transport_type)
continue
session = await stack.enter_async_context(ClientSession(read, write))

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@@ -13,34 +13,13 @@ from nanobot.bus.events import OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.channels.base import BaseChannel
from nanobot.config.schema import DiscordConfig
from nanobot.utils.helpers import split_message
DISCORD_API_BASE = "https://discord.com/api/v10"
MAX_ATTACHMENT_BYTES = 20 * 1024 * 1024 # 20MB
MAX_MESSAGE_LEN = 2000 # Discord message character limit
def _split_message(content: str, max_len: int = MAX_MESSAGE_LEN) -> list[str]:
"""Split content into chunks within max_len, preferring line breaks."""
if not content:
return []
if len(content) <= max_len:
return [content]
chunks: list[str] = []
while content:
if len(content) <= max_len:
chunks.append(content)
break
cut = content[:max_len]
pos = cut.rfind('\n')
if pos <= 0:
pos = cut.rfind(' ')
if pos <= 0:
pos = max_len
chunks.append(content[:pos])
content = content[pos:].lstrip()
return chunks
class DiscordChannel(BaseChannel):
"""Discord channel using Gateway websocket."""
@@ -54,6 +33,7 @@ class DiscordChannel(BaseChannel):
self._heartbeat_task: asyncio.Task | None = None
self._typing_tasks: dict[str, asyncio.Task] = {}
self._http: httpx.AsyncClient | None = None
self._bot_user_id: str | None = None
async def start(self) -> None:
"""Start the Discord gateway connection."""
@@ -104,7 +84,7 @@ class DiscordChannel(BaseChannel):
headers = {"Authorization": f"Bot {self.config.token}"}
try:
chunks = _split_message(msg.content or "")
chunks = split_message(msg.content or "", MAX_MESSAGE_LEN)
if not chunks:
return
@@ -170,6 +150,10 @@ class DiscordChannel(BaseChannel):
await self._identify()
elif op == 0 and event_type == "READY":
logger.info("Discord gateway READY")
# Capture bot user ID for mention detection
user_data = payload.get("user") or {}
self._bot_user_id = user_data.get("id")
logger.info("Discord bot connected as user {}", self._bot_user_id)
elif op == 0 and event_type == "MESSAGE_CREATE":
await self._handle_message_create(payload)
elif op == 7:
@@ -226,6 +210,7 @@ class DiscordChannel(BaseChannel):
sender_id = str(author.get("id", ""))
channel_id = str(payload.get("channel_id", ""))
content = payload.get("content") or ""
guild_id = payload.get("guild_id")
if not sender_id or not channel_id:
return
@@ -233,6 +218,11 @@ class DiscordChannel(BaseChannel):
if not self.is_allowed(sender_id):
return
# Check group channel policy (DMs always respond if is_allowed passes)
if guild_id is not None:
if not self._should_respond_in_group(payload, content):
return
content_parts = [content] if content else []
media_paths: list[str] = []
media_dir = Path.home() / ".nanobot" / "media"
@@ -269,11 +259,32 @@ class DiscordChannel(BaseChannel):
media=media_paths,
metadata={
"message_id": str(payload.get("id", "")),
"guild_id": payload.get("guild_id"),
"guild_id": guild_id,
"reply_to": reply_to,
},
)
def _should_respond_in_group(self, payload: dict[str, Any], content: str) -> bool:
"""Check if bot should respond in a group channel based on policy."""
if self.config.group_policy == "open":
return True
if self.config.group_policy == "mention":
# Check if bot was mentioned in the message
if self._bot_user_id:
# Check mentions array
mentions = payload.get("mentions") or []
for mention in mentions:
if str(mention.get("id")) == self._bot_user_id:
return True
# Also check content for mention format <@USER_ID>
if f"<@{self._bot_user_id}>" in content or f"<@!{self._bot_user_id}>" in content:
return True
logger.debug("Discord message in {} ignored (bot not mentioned)", payload.get("channel_id"))
return False
return True
async def _start_typing(self, channel_id: str) -> None:
"""Start periodic typing indicator for a channel."""
await self._stop_typing(channel_id)

View File

@@ -290,16 +290,28 @@ class FeishuChannel(BaseChannel):
log_level=lark.LogLevel.INFO
)
# Start WebSocket client in a separate thread with reconnect loop
# Start WebSocket client in a separate thread with reconnect loop.
# A dedicated event loop is created for this thread so that lark_oapi's
# module-level `loop = asyncio.get_event_loop()` picks up an idle loop
# instead of the already-running main asyncio loop, which would cause
# "This event loop is already running" errors.
def run_ws():
while self._running:
try:
self._ws_client.start()
except Exception as e:
logger.warning("Feishu WebSocket error: {}", e)
if self._running:
import time
time.sleep(5)
import time
import lark_oapi.ws.client as _lark_ws_client
ws_loop = asyncio.new_event_loop()
asyncio.set_event_loop(ws_loop)
# Patch the module-level loop used by lark's ws Client.start()
_lark_ws_client.loop = ws_loop
try:
while self._running:
try:
self._ws_client.start()
except Exception as e:
logger.warning("Feishu WebSocket error: {}", e)
if self._running:
time.sleep(5)
finally:
ws_loop.close()
self._ws_thread = threading.Thread(target=run_ws, daemon=True)
self._ws_thread.start()
@@ -398,6 +410,34 @@ class FeishuChannel(BaseChannel):
elements.extend(self._split_headings(remaining))
return elements or [{"tag": "markdown", "content": content}]
@staticmethod
def _split_elements_by_table_limit(elements: list[dict], max_tables: int = 1) -> list[list[dict]]:
"""Split card elements into groups with at most *max_tables* table elements each.
Feishu cards have a hard limit of one table per card (API error 11310).
When the rendered content contains multiple markdown tables each table is
placed in a separate card message so every table reaches the user.
"""
if not elements:
return [[]]
groups: list[list[dict]] = []
current: list[dict] = []
table_count = 0
for el in elements:
if el.get("tag") == "table":
if table_count >= max_tables:
if current:
groups.append(current)
current = []
table_count = 0
current.append(el)
table_count += 1
else:
current.append(el)
if current:
groups.append(current)
return groups or [[]]
def _split_headings(self, content: str) -> list[dict]:
"""Split content by headings, converting headings to div elements."""
protected = content
@@ -432,8 +472,124 @@ class FeishuChannel(BaseChannel):
return elements or [{"tag": "markdown", "content": content}]
# ── Smart format detection ──────────────────────────────────────────
# Patterns that indicate "complex" markdown needing card rendering
_COMPLEX_MD_RE = re.compile(
r"```" # fenced code block
r"|^\|.+\|.*\n\s*\|[-:\s|]+\|" # markdown table (header + separator)
r"|^#{1,6}\s+" # headings
, re.MULTILINE,
)
# Simple markdown patterns (bold, italic, strikethrough)
_SIMPLE_MD_RE = re.compile(
r"\*\*.+?\*\*" # **bold**
r"|__.+?__" # __bold__
r"|(?<!\*)\*(?!\*)(.+?)(?<!\*)\*(?!\*)" # *italic* (single *)
r"|~~.+?~~" # ~~strikethrough~~
, re.DOTALL,
)
# Markdown link: [text](url)
_MD_LINK_RE = re.compile(r"\[([^\]]+)\]\((https?://[^\)]+)\)")
# Unordered list items
_LIST_RE = re.compile(r"^[\s]*[-*+]\s+", re.MULTILINE)
# Ordered list items
_OLIST_RE = re.compile(r"^[\s]*\d+\.\s+", re.MULTILINE)
# Max length for plain text format
_TEXT_MAX_LEN = 200
# Max length for post (rich text) format; beyond this, use card
_POST_MAX_LEN = 2000
@classmethod
def _detect_msg_format(cls, content: str) -> str:
"""Determine the optimal Feishu message format for *content*.
Returns one of:
- ``"text"`` plain text, short and no markdown
- ``"post"`` rich text (links only, moderate length)
- ``"interactive"`` card with full markdown rendering
"""
stripped = content.strip()
# Complex markdown (code blocks, tables, headings) → always card
if cls._COMPLEX_MD_RE.search(stripped):
return "interactive"
# Long content → card (better readability with card layout)
if len(stripped) > cls._POST_MAX_LEN:
return "interactive"
# Has bold/italic/strikethrough → card (post format can't render these)
if cls._SIMPLE_MD_RE.search(stripped):
return "interactive"
# Has list items → card (post format can't render list bullets well)
if cls._LIST_RE.search(stripped) or cls._OLIST_RE.search(stripped):
return "interactive"
# Has links → post format (supports <a> tags)
if cls._MD_LINK_RE.search(stripped):
return "post"
# Short plain text → text format
if len(stripped) <= cls._TEXT_MAX_LEN:
return "text"
# Medium plain text without any formatting → post format
return "post"
@classmethod
def _markdown_to_post(cls, content: str) -> str:
"""Convert markdown content to Feishu post message JSON.
Handles links ``[text](url)`` as ``a`` tags; everything else as ``text`` tags.
Each line becomes a paragraph (row) in the post body.
"""
lines = content.strip().split("\n")
paragraphs: list[list[dict]] = []
for line in lines:
elements: list[dict] = []
last_end = 0
for m in cls._MD_LINK_RE.finditer(line):
# Text before this link
before = line[last_end:m.start()]
if before:
elements.append({"tag": "text", "text": before})
elements.append({
"tag": "a",
"text": m.group(1),
"href": m.group(2),
})
last_end = m.end()
# Remaining text after last link
remaining = line[last_end:]
if remaining:
elements.append({"tag": "text", "text": remaining})
# Empty line → empty paragraph for spacing
if not elements:
elements.append({"tag": "text", "text": ""})
paragraphs.append(elements)
post_body = {
"zh_cn": {
"content": paragraphs,
}
}
return json.dumps(post_body, ensure_ascii=False)
_IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".gif", ".bmp", ".webp", ".ico", ".tiff", ".tif"}
_AUDIO_EXTS = {".opus"}
_VIDEO_EXTS = {".mp4", ".mov", ".avi"}
_FILE_TYPE_MAP = {
".opus": "opus", ".mp4": "mp4", ".pdf": "pdf", ".doc": "doc", ".docx": "doc",
".xls": "xls", ".xlsx": "xls", ".ppt": "ppt", ".pptx": "ppt",
@@ -642,18 +798,45 @@ class FeishuChannel(BaseChannel):
else:
key = await loop.run_in_executor(None, self._upload_file_sync, file_path)
if key:
media_type = "audio" if ext in self._AUDIO_EXTS else "file"
# Use msg_type "media" for audio/video so users can play inline;
# "file" for everything else (documents, archives, etc.)
if ext in self._AUDIO_EXTS or ext in self._VIDEO_EXTS:
media_type = "media"
else:
media_type = "file"
await loop.run_in_executor(
None, self._send_message_sync,
receive_id_type, msg.chat_id, media_type, json.dumps({"file_key": key}, ensure_ascii=False),
)
if msg.content and msg.content.strip():
card = {"config": {"wide_screen_mode": True}, "elements": self._build_card_elements(msg.content)}
await loop.run_in_executor(
None, self._send_message_sync,
receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False),
)
fmt = self._detect_msg_format(msg.content)
if fmt == "text":
# Short plain text send as simple text message
text_body = json.dumps({"text": msg.content.strip()}, ensure_ascii=False)
await loop.run_in_executor(
None, self._send_message_sync,
receive_id_type, msg.chat_id, "text", text_body,
)
elif fmt == "post":
# Medium content with links send as rich-text post
post_body = self._markdown_to_post(msg.content)
await loop.run_in_executor(
None, self._send_message_sync,
receive_id_type, msg.chat_id, "post", post_body,
)
else:
# Complex / long content send as interactive card
elements = self._build_card_elements(msg.content)
for chunk in self._split_elements_by_table_limit(elements):
card = {"config": {"wide_screen_mode": True}, "elements": chunk}
await loop.run_in_executor(
None, self._send_message_sync,
receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False),
)
except Exception as e:
logger.error("Error sending Feishu message: {}", e)

View File

@@ -14,6 +14,9 @@ from nanobot.bus.events import OutboundMessage
from nanobot.bus.queue import MessageBus
from nanobot.channels.base import BaseChannel
from nanobot.config.schema import TelegramConfig
from nanobot.utils.helpers import split_message
TELEGRAM_MAX_MESSAGE_LEN = 4000 # Telegram message character limit
def _markdown_to_telegram_html(text: str) -> str:
@@ -79,26 +82,6 @@ def _markdown_to_telegram_html(text: str) -> str:
return text
def _split_message(content: str, max_len: int = 4000) -> list[str]:
"""Split content into chunks within max_len, preferring line breaks."""
if len(content) <= max_len:
return [content]
chunks: list[str] = []
while content:
if len(content) <= max_len:
chunks.append(content)
break
cut = content[:max_len]
pos = cut.rfind('\n')
if pos == -1:
pos = cut.rfind(' ')
if pos == -1:
pos = max_len
chunks.append(content[:pos])
content = content[pos:].lstrip()
return chunks
class TelegramChannel(BaseChannel):
"""
Telegram channel using long polling.
@@ -225,7 +208,9 @@ class TelegramChannel(BaseChannel):
logger.warning("Telegram bot not running")
return
self._stop_typing(msg.chat_id)
# Only stop typing indicator for final responses
if not msg.metadata.get("_progress", False):
self._stop_typing(msg.chat_id)
try:
chat_id = int(msg.chat_id)
@@ -269,23 +254,41 @@ class TelegramChannel(BaseChannel):
# Send text content
if msg.content and msg.content != "[empty message]":
for chunk in _split_message(msg.content):
is_progress = msg.metadata.get("_progress", False)
draft_id = msg.metadata.get("message_id")
for chunk in split_message(msg.content, TELEGRAM_MAX_MESSAGE_LEN):
try:
html = _markdown_to_telegram_html(chunk)
await self._app.bot.send_message(
chat_id=chat_id,
text=html,
parse_mode="HTML",
reply_parameters=reply_params
)
if is_progress and draft_id:
await self._app.bot.send_message_draft(
chat_id=chat_id,
draft_id=draft_id,
text=html,
parse_mode="HTML"
)
else:
await self._app.bot.send_message(
chat_id=chat_id,
text=html,
parse_mode="HTML",
reply_parameters=reply_params
)
except Exception as e:
logger.warning("HTML parse failed, falling back to plain text: {}", e)
try:
await self._app.bot.send_message(
chat_id=chat_id,
text=chunk,
reply_parameters=reply_params
)
if is_progress and draft_id:
await self._app.bot.send_message_draft(
chat_id=chat_id,
draft_id=draft_id,
text=chunk
)
else:
await self._app.bot.send_message(
chat_id=chat_id,
text=chunk,
reply_parameters=reply_params
)
except Exception as e2:
logger.error("Error sending Telegram message: {}", e2)

View File

@@ -7,6 +7,18 @@ import signal
import sys
from pathlib import Path
# Force UTF-8 encoding for Windows console
if sys.platform == "win32":
import locale
if sys.stdout.encoding != "utf-8":
os.environ["PYTHONIOENCODING"] = "utf-8"
# Re-open stdout/stderr with UTF-8 encoding
try:
sys.stdout.reconfigure(encoding="utf-8", errors="replace")
sys.stderr.reconfigure(encoding="utf-8", errors="replace")
except Exception:
pass
import typer
from prompt_toolkit import PromptSession
from prompt_toolkit.formatted_text import HTML
@@ -244,13 +256,15 @@ def _make_provider(config: Config):
@app.command()
def gateway(
port: int = typer.Option(18790, "--port", "-p", help="Gateway port"),
workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
config: str | None = typer.Option(None, "--config", "-c", help="Config file path"),
verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
):
"""Start the nanobot gateway."""
from nanobot.agent.loop import AgentLoop
from nanobot.bus.queue import MessageBus
from nanobot.channels.manager import ChannelManager
from nanobot.config.loader import get_data_dir, load_config
from nanobot.config.loader import load_config
from nanobot.cron.service import CronService
from nanobot.cron.types import CronJob
from nanobot.heartbeat.service import HeartbeatService
@@ -260,16 +274,20 @@ def gateway(
import logging
logging.basicConfig(level=logging.DEBUG)
console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
config_path = Path(config) if config else None
config = load_config(config_path)
if workspace:
config.agents.defaults.workspace = workspace
config = load_config()
console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
sync_workspace_templates(config.workspace_path)
bus = MessageBus()
provider = _make_provider(config)
session_manager = SessionManager(config.workspace_path)
# Create cron service first (callback set after agent creation)
cron_store_path = get_data_dir() / "cron" / "jobs.json"
# Use workspace path for per-instance cron store
cron_store_path = config.workspace_path / "cron" / "jobs.json"
cron = CronService(cron_store_path)
# Create agent with cron service
@@ -511,12 +529,21 @@ def agent(
else:
cli_channel, cli_chat_id = "cli", session_id
def _exit_on_sigint(signum, frame):
def _handle_signal(signum, frame):
sig_name = signal.Signals(signum).name
_restore_terminal()
console.print("\nGoodbye!")
os._exit(0)
console.print(f"\nReceived {sig_name}, goodbye!")
sys.exit(0)
signal.signal(signal.SIGINT, _exit_on_sigint)
signal.signal(signal.SIGINT, _handle_signal)
signal.signal(signal.SIGTERM, _handle_signal)
# SIGHUP is not available on Windows
if hasattr(signal, 'SIGHUP'):
signal.signal(signal.SIGHUP, _handle_signal)
# Ignore SIGPIPE to prevent silent process termination when writing to closed pipes
# SIGPIPE is not available on Windows
if hasattr(signal, 'SIGPIPE'):
signal.signal(signal.SIGPIPE, signal.SIG_IGN)
async def run_interactive():
bus_task = asyncio.create_task(agent_loop.run())

View File

@@ -29,7 +29,9 @@ class TelegramConfig(Base):
enabled: bool = False
token: str = "" # Bot token from @BotFather
allow_from: list[str] = Field(default_factory=list) # Allowed user IDs or usernames
proxy: str | None = None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
proxy: str | None = (
None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
)
reply_to_message: bool = False # If true, bot replies quote the original message
@@ -42,7 +44,9 @@ class FeishuConfig(Base):
encrypt_key: str = "" # Encrypt Key for event subscription (optional)
verification_token: str = "" # Verification Token for event subscription (optional)
allow_from: list[str] = Field(default_factory=list) # Allowed user open_ids
react_emoji: str = "THUMBSUP" # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
react_emoji: str = (
"THUMBSUP" # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
)
class DingTalkConfig(Base):
@@ -62,6 +66,7 @@ class DiscordConfig(Base):
allow_from: list[str] = Field(default_factory=list) # Allowed user IDs
gateway_url: str = "wss://gateway.discord.gg/?v=10&encoding=json"
intents: int = 37377 # GUILDS + GUILD_MESSAGES + DIRECT_MESSAGES + MESSAGE_CONTENT
group_policy: Literal["mention", "open"] = "mention"
class MatrixConfig(Base):
@@ -72,9 +77,13 @@ class MatrixConfig(Base):
access_token: str = ""
user_id: str = "" # @bot:matrix.org
device_id: str = ""
e2ee_enabled: bool = True # Enable Matrix E2EE support (encryption + encrypted room handling).
sync_stop_grace_seconds: int = 2 # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
max_media_bytes: int = 20 * 1024 * 1024 # Max attachment size accepted for Matrix media handling (inbound + outbound).
e2ee_enabled: bool = True # Enable Matrix E2EE support (encryption + encrypted room handling).
sync_stop_grace_seconds: int = (
2 # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
)
max_media_bytes: int = (
20 * 1024 * 1024
) # Max attachment size accepted for Matrix media handling (inbound + outbound).
allow_from: list[str] = Field(default_factory=list)
group_policy: Literal["open", "mention", "allowlist"] = "open"
group_allow_from: list[str] = Field(default_factory=list)
@@ -105,7 +114,9 @@ class EmailConfig(Base):
from_address: str = ""
# Behavior
auto_reply_enabled: bool = True # If false, inbound email is read but no automatic reply is sent
auto_reply_enabled: bool = (
True # If false, inbound email is read but no automatic reply is sent
)
poll_interval_seconds: int = 30
mark_seen: bool = True
max_body_chars: int = 12000
@@ -183,27 +194,17 @@ class QQConfig(Base):
enabled: bool = False
app_id: str = "" # 机器人 ID (AppID) from q.qq.com
secret: str = "" # 机器人密钥 (AppSecret) from q.qq.com
allow_from: list[str] = Field(default_factory=list) # Allowed user openids (empty = public access)
allow_from: list[str] = Field(
default_factory=list
) # Allowed user openids (empty = public access)
class MatrixConfig(Base):
"""Matrix (Element) channel configuration."""
enabled: bool = False
homeserver: str = "https://matrix.org"
access_token: str = ""
user_id: str = "" # e.g. @bot:matrix.org
device_id: str = ""
e2ee_enabled: bool = True # end-to-end encryption support
sync_stop_grace_seconds: int = 2 # graceful sync_forever shutdown timeout
max_media_bytes: int = 20 * 1024 * 1024 # inbound + outbound attachment limit
allow_from: list[str] = Field(default_factory=list)
group_policy: Literal["open", "mention", "allowlist"] = "open"
group_allow_from: list[str] = Field(default_factory=list)
allow_room_mentions: bool = False
class ChannelsConfig(Base):
"""Configuration for chat channels."""
send_progress: bool = True # stream agent's text progress to the channel
send_progress: bool = True # stream agent's text progress to the channel
send_tool_hints: bool = False # stream tool-call hints (e.g. read_file("…"))
whatsapp: WhatsAppConfig = Field(default_factory=WhatsAppConfig)
telegram: TelegramConfig = Field(default_factory=TelegramConfig)
@@ -222,7 +223,9 @@ class AgentDefaults(Base):
workspace: str = "~/.nanobot/workspace"
model: str = "anthropic/claude-opus-4-5"
provider: str = "auto" # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
provider: str = (
"auto" # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
)
max_tokens: int = 8192
temperature: float = 0.1
max_tool_iterations: int = 40
@@ -260,8 +263,8 @@ class ProvidersConfig(Base):
moonshot: ProviderConfig = Field(default_factory=ProviderConfig)
minimax: ProviderConfig = Field(default_factory=ProviderConfig)
aihubmix: ProviderConfig = Field(default_factory=ProviderConfig) # AiHubMix API gateway
siliconflow: ProviderConfig = Field(default_factory=ProviderConfig) # SiliconFlow (硅基流动) API gateway
volcengine: ProviderConfig = Field(default_factory=ProviderConfig) # VolcEngine (火山引擎) API gateway
siliconflow: ProviderConfig = Field(default_factory=ProviderConfig) # SiliconFlow (硅基流动)
volcengine: ProviderConfig = Field(default_factory=ProviderConfig) # VolcEngine (火山引擎)
openai_codex: ProviderConfig = Field(default_factory=ProviderConfig) # OpenAI Codex (OAuth)
github_copilot: ProviderConfig = Field(default_factory=ProviderConfig) # Github Copilot (OAuth)
@@ -291,7 +294,9 @@ class WebSearchConfig(Base):
class WebToolsConfig(Base):
"""Web tools configuration."""
proxy: str | None = None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
proxy: str | None = (
None # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
)
search: WebSearchConfig = Field(default_factory=WebSearchConfig)
@@ -305,12 +310,13 @@ class ExecToolConfig(Base):
class MCPServerConfig(Base):
"""MCP server connection configuration (stdio or HTTP)."""
type: Literal["stdio", "sse", "streamableHttp"] | None = None # auto-detected if omitted
command: str = "" # Stdio: command to run (e.g. "npx")
args: list[str] = Field(default_factory=list) # Stdio: command arguments
env: dict[str, str] = Field(default_factory=dict) # Stdio: extra env vars
url: str = "" # HTTP: streamable HTTP endpoint URL
headers: dict[str, str] = Field(default_factory=dict) # HTTP: Custom HTTP Headers
tool_timeout: int = 30 # Seconds before a tool call is cancelled
url: str = "" # HTTP/SSE: endpoint URL
headers: dict[str, str] = Field(default_factory=dict) # HTTP/SSE: custom headers
tool_timeout: int = 30 # seconds before a tool call is cancelled
class ToolsConfig(Base):
@@ -336,7 +342,9 @@ class Config(BaseSettings):
"""Get expanded workspace path."""
return Path(self.agents.defaults.workspace).expanduser()
def _match_provider(self, model: str | None = None) -> tuple["ProviderConfig | None", str | None]:
def _match_provider(
self, model: str | None = None
) -> tuple["ProviderConfig | None", str | None]:
"""Match provider config and its registry name. Returns (config, spec_name)."""
from nanobot.providers.registry import PROVIDERS

View File

@@ -2,6 +2,7 @@
from __future__ import annotations
import uuid
from typing import Any
import json_repair
@@ -15,7 +16,12 @@ class CustomProvider(LLMProvider):
def __init__(self, api_key: str = "no-key", api_base: str = "http://localhost:8000/v1", default_model: str = "default"):
super().__init__(api_key, api_base)
self.default_model = default_model
self._client = AsyncOpenAI(api_key=api_key, base_url=api_base)
# Keep affinity stable for this provider instance to improve backend cache locality.
self._client = AsyncOpenAI(
api_key=api_key,
base_url=api_base,
default_headers={"x-session-affinity": uuid.uuid4().hex},
)
async def chat(self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7,

View File

@@ -8,6 +8,7 @@ from typing import Any
import json_repair
import litellm
from litellm import acompletion
from loguru import logger
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from nanobot.providers.registry import find_by_model, find_gateway
@@ -255,20 +256,37 @@ class LiteLLMProvider(LLMProvider):
"""Parse LiteLLM response into our standard format."""
choice = response.choices[0]
message = choice.message
content = message.content
finish_reason = choice.finish_reason
# Some providers (e.g. GitHub Copilot) split content and tool_calls
# across multiple choices. Merge them so tool_calls are not lost.
raw_tool_calls = []
for ch in response.choices:
msg = ch.message
if hasattr(msg, "tool_calls") and msg.tool_calls:
raw_tool_calls.extend(msg.tool_calls)
if ch.finish_reason in ("tool_calls", "stop"):
finish_reason = ch.finish_reason
if not content and msg.content:
content = msg.content
if len(response.choices) > 1:
logger.debug("LiteLLM response has {} choices, merged {} tool_calls",
len(response.choices), len(raw_tool_calls))
tool_calls = []
if hasattr(message, "tool_calls") and message.tool_calls:
for tc in message.tool_calls:
# Parse arguments from JSON string if needed
args = tc.function.arguments
if isinstance(args, str):
args = json_repair.loads(args)
for tc in raw_tool_calls:
# Parse arguments from JSON string if needed
args = tc.function.arguments
if isinstance(args, str):
args = json_repair.loads(args)
tool_calls.append(ToolCallRequest(
id=_short_tool_id(),
name=tc.function.name,
arguments=args,
))
tool_calls.append(ToolCallRequest(
id=_short_tool_id(),
name=tc.function.name,
arguments=args,
))
usage = {}
if hasattr(response, "usage") and response.usage:
@@ -280,11 +298,11 @@ class LiteLLMProvider(LLMProvider):
reasoning_content = getattr(message, "reasoning_content", None) or None
thinking_blocks = getattr(message, "thinking_blocks", None) or None
return LLMResponse(
content=message.content,
content=content,
tool_calls=tool_calls,
finish_reason=choice.finish_reason or "stop",
finish_reason=finish_reason or "stop",
usage=usage,
reasoning_content=reasoning_content,
thinking_blocks=thinking_blocks,

View File

@@ -26,33 +26,33 @@ class ProviderSpec:
"""
# identity
name: str # config field name, e.g. "dashscope"
keywords: tuple[str, ...] # model-name keywords for matching (lowercase)
env_key: str # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
display_name: str = "" # shown in `nanobot status`
name: str # config field name, e.g. "dashscope"
keywords: tuple[str, ...] # model-name keywords for matching (lowercase)
env_key: str # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
display_name: str = "" # shown in `nanobot status`
# model prefixing
litellm_prefix: str = "" # "dashscope" → model becomes "dashscope/{model}"
skip_prefixes: tuple[str, ...] = () # don't prefix if model already starts with these
litellm_prefix: str = "" # "dashscope" → model becomes "dashscope/{model}"
skip_prefixes: tuple[str, ...] = () # don't prefix if model already starts with these
# extra env vars, e.g. (("ZHIPUAI_API_KEY", "{api_key}"),)
env_extras: tuple[tuple[str, str], ...] = ()
# gateway / local detection
is_gateway: bool = False # routes any model (OpenRouter, AiHubMix)
is_local: bool = False # local deployment (vLLM, Ollama)
detect_by_key_prefix: str = "" # match api_key prefix, e.g. "sk-or-"
detect_by_base_keyword: str = "" # match substring in api_base URL
default_api_base: str = "" # fallback base URL
is_gateway: bool = False # routes any model (OpenRouter, AiHubMix)
is_local: bool = False # local deployment (vLLM, Ollama)
detect_by_key_prefix: str = "" # match api_key prefix, e.g. "sk-or-"
detect_by_base_keyword: str = "" # match substring in api_base URL
default_api_base: str = "" # fallback base URL
# gateway behavior
strip_model_prefix: bool = False # strip "provider/" before re-prefixing
strip_model_prefix: bool = False # strip "provider/" before re-prefixing
# per-model param overrides, e.g. (("kimi-k2.5", {"temperature": 1.0}),)
model_overrides: tuple[tuple[str, dict[str, Any]], ...] = ()
# OAuth-based providers (e.g., OpenAI Codex) don't use API keys
is_oauth: bool = False # if True, uses OAuth flow instead of API key
is_oauth: bool = False # if True, uses OAuth flow instead of API key
# Direct providers bypass LiteLLM entirely (e.g., CustomProvider)
is_direct: bool = False
@@ -70,7 +70,6 @@ class ProviderSpec:
# ---------------------------------------------------------------------------
PROVIDERS: tuple[ProviderSpec, ...] = (
# === Custom (direct OpenAI-compatible endpoint, bypasses LiteLLM) ======
ProviderSpec(
name="custom",
@@ -80,17 +79,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
litellm_prefix="",
is_direct=True,
),
# === Gateways (detected by api_key / api_base, not model name) =========
# Gateways can route any model, so they win in fallback.
# OpenRouter: global gateway, keys start with "sk-or-"
ProviderSpec(
name="openrouter",
keywords=("openrouter",),
env_key="OPENROUTER_API_KEY",
display_name="OpenRouter",
litellm_prefix="openrouter", # claude-3 → openrouter/claude-3
litellm_prefix="openrouter", # claude-3 → openrouter/claude-3
skip_prefixes=(),
env_extras=(),
is_gateway=True,
@@ -102,16 +99,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
model_overrides=(),
supports_prompt_caching=True,
),
# AiHubMix: global gateway, OpenAI-compatible interface.
# strip_model_prefix=True: it doesn't understand "anthropic/claude-3",
# so we strip to bare "claude-3" then re-prefix as "openai/claude-3".
ProviderSpec(
name="aihubmix",
keywords=("aihubmix",),
env_key="OPENAI_API_KEY", # OpenAI-compatible
env_key="OPENAI_API_KEY", # OpenAI-compatible
display_name="AiHubMix",
litellm_prefix="openai", # → openai/{model}
litellm_prefix="openai", # → openai/{model}
skip_prefixes=(),
env_extras=(),
is_gateway=True,
@@ -119,10 +115,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
detect_by_key_prefix="",
detect_by_base_keyword="aihubmix",
default_api_base="https://aihubmix.com/v1",
strip_model_prefix=True, # anthropic/claude-3 → claude-3 → openai/claude-3
strip_model_prefix=True, # anthropic/claude-3 → claude-3 → openai/claude-3
model_overrides=(),
),
# SiliconFlow (硅基流动): OpenAI-compatible gateway, model names keep org prefix
ProviderSpec(
name="siliconflow",
@@ -140,7 +135,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# VolcEngine (火山引擎): OpenAI-compatible gateway
ProviderSpec(
name="volcengine",
@@ -158,9 +152,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# === Standard providers (matched by model-name keywords) ===============
# Anthropic: LiteLLM recognizes "claude-*" natively, no prefix needed.
ProviderSpec(
name="anthropic",
@@ -179,7 +171,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
model_overrides=(),
supports_prompt_caching=True,
),
# OpenAI: LiteLLM recognizes "gpt-*" natively, no prefix needed.
ProviderSpec(
name="openai",
@@ -197,14 +188,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# OpenAI Codex: uses OAuth, not API key.
ProviderSpec(
name="openai_codex",
keywords=("openai-codex",),
env_key="", # OAuth-based, no API key
env_key="", # OAuth-based, no API key
display_name="OpenAI Codex",
litellm_prefix="", # Not routed through LiteLLM
litellm_prefix="", # Not routed through LiteLLM
skip_prefixes=(),
env_extras=(),
is_gateway=False,
@@ -214,16 +204,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
default_api_base="https://chatgpt.com/backend-api",
strip_model_prefix=False,
model_overrides=(),
is_oauth=True, # OAuth-based authentication
is_oauth=True, # OAuth-based authentication
),
# Github Copilot: uses OAuth, not API key.
ProviderSpec(
name="github_copilot",
keywords=("github_copilot", "copilot"),
env_key="", # OAuth-based, no API key
env_key="", # OAuth-based, no API key
display_name="Github Copilot",
litellm_prefix="github_copilot", # github_copilot/model → github_copilot/model
litellm_prefix="github_copilot", # github_copilot/model → github_copilot/model
skip_prefixes=("github_copilot/",),
env_extras=(),
is_gateway=False,
@@ -233,17 +222,16 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
default_api_base="",
strip_model_prefix=False,
model_overrides=(),
is_oauth=True, # OAuth-based authentication
is_oauth=True, # OAuth-based authentication
),
# DeepSeek: needs "deepseek/" prefix for LiteLLM routing.
ProviderSpec(
name="deepseek",
keywords=("deepseek",),
env_key="DEEPSEEK_API_KEY",
display_name="DeepSeek",
litellm_prefix="deepseek", # deepseek-chat → deepseek/deepseek-chat
skip_prefixes=("deepseek/",), # avoid double-prefix
litellm_prefix="deepseek", # deepseek-chat → deepseek/deepseek-chat
skip_prefixes=("deepseek/",), # avoid double-prefix
env_extras=(),
is_gateway=False,
is_local=False,
@@ -253,15 +241,14 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# Gemini: needs "gemini/" prefix for LiteLLM.
ProviderSpec(
name="gemini",
keywords=("gemini",),
env_key="GEMINI_API_KEY",
display_name="Gemini",
litellm_prefix="gemini", # gemini-pro → gemini/gemini-pro
skip_prefixes=("gemini/",), # avoid double-prefix
litellm_prefix="gemini", # gemini-pro → gemini/gemini-pro
skip_prefixes=("gemini/",), # avoid double-prefix
env_extras=(),
is_gateway=False,
is_local=False,
@@ -271,7 +258,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# Zhipu: LiteLLM uses "zai/" prefix.
# Also mirrors key to ZHIPUAI_API_KEY (some LiteLLM paths check that).
# skip_prefixes: don't add "zai/" when already routed via gateway.
@@ -280,11 +266,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
keywords=("zhipu", "glm", "zai"),
env_key="ZAI_API_KEY",
display_name="Zhipu AI",
litellm_prefix="zai", # glm-4 → zai/glm-4
litellm_prefix="zai", # glm-4 → zai/glm-4
skip_prefixes=("zhipu/", "zai/", "openrouter/", "hosted_vllm/"),
env_extras=(
("ZHIPUAI_API_KEY", "{api_key}"),
),
env_extras=(("ZHIPUAI_API_KEY", "{api_key}"),),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
@@ -293,14 +277,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# DashScope: Qwen models, needs "dashscope/" prefix.
ProviderSpec(
name="dashscope",
keywords=("qwen", "dashscope"),
env_key="DASHSCOPE_API_KEY",
display_name="DashScope",
litellm_prefix="dashscope", # qwen-max → dashscope/qwen-max
litellm_prefix="dashscope", # qwen-max → dashscope/qwen-max
skip_prefixes=("dashscope/", "openrouter/"),
env_extras=(),
is_gateway=False,
@@ -311,7 +294,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# Moonshot: Kimi models, needs "moonshot/" prefix.
# LiteLLM requires MOONSHOT_API_BASE env var to find the endpoint.
# Kimi K2.5 API enforces temperature >= 1.0.
@@ -320,22 +302,17 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
keywords=("moonshot", "kimi"),
env_key="MOONSHOT_API_KEY",
display_name="Moonshot",
litellm_prefix="moonshot", # kimi-k2.5 → moonshot/kimi-k2.5
litellm_prefix="moonshot", # kimi-k2.5 → moonshot/kimi-k2.5
skip_prefixes=("moonshot/", "openrouter/"),
env_extras=(
("MOONSHOT_API_BASE", "{api_base}"),
),
env_extras=(("MOONSHOT_API_BASE", "{api_base}"),),
is_gateway=False,
is_local=False,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="https://api.moonshot.ai/v1", # intl; use api.moonshot.cn for China
default_api_base="https://api.moonshot.ai/v1", # intl; use api.moonshot.cn for China
strip_model_prefix=False,
model_overrides=(
("kimi-k2.5", {"temperature": 1.0}),
),
model_overrides=(("kimi-k2.5", {"temperature": 1.0}),),
),
# MiniMax: needs "minimax/" prefix for LiteLLM routing.
# Uses OpenAI-compatible API at api.minimax.io/v1.
ProviderSpec(
@@ -343,7 +320,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
keywords=("minimax",),
env_key="MINIMAX_API_KEY",
display_name="MiniMax",
litellm_prefix="minimax", # MiniMax-M2.1 → minimax/MiniMax-M2.1
litellm_prefix="minimax", # MiniMax-M2.1 → minimax/MiniMax-M2.1
skip_prefixes=("minimax/", "openrouter/"),
env_extras=(),
is_gateway=False,
@@ -354,9 +331,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
),
# === Local deployment (matched by config key, NOT by api_base) =========
# vLLM / any OpenAI-compatible local server.
# Detected when config key is "vllm" (provider_name="vllm").
ProviderSpec(
@@ -364,20 +339,18 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
keywords=("vllm",),
env_key="HOSTED_VLLM_API_KEY",
display_name="vLLM/Local",
litellm_prefix="hosted_vllm", # Llama-3-8B → hosted_vllm/Llama-3-8B
litellm_prefix="hosted_vllm", # Llama-3-8B → hosted_vllm/Llama-3-8B
skip_prefixes=(),
env_extras=(),
is_gateway=False,
is_local=True,
detect_by_key_prefix="",
detect_by_base_keyword="",
default_api_base="", # user must provide in config
default_api_base="", # user must provide in config
strip_model_prefix=False,
model_overrides=(),
),
# === Auxiliary (not a primary LLM provider) ============================
# Groq: mainly used for Whisper voice transcription, also usable for LLM.
# Needs "groq/" prefix for LiteLLM routing. Placed last — it rarely wins fallback.
ProviderSpec(
@@ -385,8 +358,8 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
keywords=("groq",),
env_key="GROQ_API_KEY",
display_name="Groq",
litellm_prefix="groq", # llama3-8b-8192 → groq/llama3-8b-8192
skip_prefixes=("groq/",), # avoid double-prefix
litellm_prefix="groq", # llama3-8b-8192 → groq/llama3-8b-8192
skip_prefixes=("groq/",), # avoid double-prefix
env_extras=(),
is_gateway=False,
is_local=False,
@@ -403,6 +376,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
# Lookup helpers
# ---------------------------------------------------------------------------
def find_by_model(model: str) -> ProviderSpec | None:
"""Match a standard provider by model-name keyword (case-insensitive).
Skips gateways/local — those are matched by api_key/api_base instead."""
@@ -418,7 +392,9 @@ def find_by_model(model: str) -> ProviderSpec | None:
return spec
for spec in std_specs:
if any(kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords):
if any(
kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords
):
return spec
return None

View File

@@ -5,6 +5,19 @@ from datetime import datetime
from pathlib import Path
def detect_image_mime(data: bytes) -> str | None:
"""Detect image MIME type from magic bytes, ignoring file extension."""
if data[:8] == b"\x89PNG\r\n\x1a\n":
return "image/png"
if data[:3] == b"\xff\xd8\xff":
return "image/jpeg"
if data[:6] in (b"GIF87a", b"GIF89a"):
return "image/gif"
if data[:4] == b"RIFF" and data[8:12] == b"WEBP":
return "image/webp"
return None
def ensure_dir(path: Path) -> Path:
"""Ensure directory exists, return it."""
path.mkdir(parents=True, exist_ok=True)
@@ -34,6 +47,38 @@ def safe_filename(name: str) -> str:
return _UNSAFE_CHARS.sub("_", name).strip()
def split_message(content: str, max_len: int = 2000) -> list[str]:
"""
Split content into chunks within max_len, preferring line breaks.
Args:
content: The text content to split.
max_len: Maximum length per chunk (default 2000 for Discord compatibility).
Returns:
List of message chunks, each within max_len.
"""
if not content:
return []
if len(content) <= max_len:
return [content]
chunks: list[str] = []
while content:
if len(content) <= max_len:
chunks.append(content)
break
cut = content[:max_len]
# Try to break at newline first, then space, then hard break
pos = cut.rfind('\n')
if pos <= 0:
pos = cut.rfind(' ')
if pos <= 0:
pos = max_len
chunks.append(content[:pos])
content = content[pos:].lstrip()
return chunks
def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]:
"""Sync bundled templates to workspace. Only creates missing files."""
from importlib.resources import files as pkg_files

View File

@@ -30,7 +30,7 @@ dependencies = [
"rich>=14.0.0,<15.0.0",
"croniter>=6.0.0,<7.0.0",
"dingtalk-stream>=0.24.0,<1.0.0",
"python-telegram-bot[socks]>=22.0,<23.0",
"python-telegram-bot[socks]>=22.6,<23.0",
"lark-oapi>=1.5.0,<2.0.0",
"socksio>=1.0.0,<2.0.0",
"python-socketio>=5.16.0,<6.0.0",

View File

@@ -0,0 +1,104 @@
"""Tests for FeishuChannel._split_elements_by_table_limit.
Feishu cards reject messages that contain more than one table element
(API error 11310: card table number over limit). The helper splits a flat
list of card elements into groups so that each group contains at most one
table, allowing nanobot to send multiple cards instead of failing.
"""
from nanobot.channels.feishu import FeishuChannel
def _md(text: str) -> dict:
return {"tag": "markdown", "content": text}
def _table() -> dict:
return {
"tag": "table",
"columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
"rows": [{"c0": "v"}],
"page_size": 2,
}
split = FeishuChannel._split_elements_by_table_limit
def test_empty_list_returns_single_empty_group() -> None:
assert split([]) == [[]]
def test_no_tables_returns_single_group() -> None:
els = [_md("hello"), _md("world")]
result = split(els)
assert result == [els]
def test_single_table_stays_in_one_group() -> None:
els = [_md("intro"), _table(), _md("outro")]
result = split(els)
assert len(result) == 1
assert result[0] == els
def test_two_tables_split_into_two_groups() -> None:
# Use different row values so the two tables are not equal
t1 = {
"tag": "table",
"columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
"rows": [{"c0": "table-one"}],
"page_size": 2,
}
t2 = {
"tag": "table",
"columns": [{"tag": "column", "name": "c0", "display_name": "B", "width": "auto"}],
"rows": [{"c0": "table-two"}],
"page_size": 2,
}
els = [_md("before"), t1, _md("between"), t2, _md("after")]
result = split(els)
assert len(result) == 2
# First group: text before table-1 + table-1
assert t1 in result[0]
assert t2 not in result[0]
# Second group: text between tables + table-2 + text after
assert t2 in result[1]
assert t1 not in result[1]
def test_three_tables_split_into_three_groups() -> None:
tables = [
{"tag": "table", "columns": [], "rows": [{"c0": f"t{i}"}], "page_size": 1}
for i in range(3)
]
els = tables[:]
result = split(els)
assert len(result) == 3
for i, group in enumerate(result):
assert tables[i] in group
def test_leading_markdown_stays_with_first_table() -> None:
intro = _md("intro")
t = _table()
result = split([intro, t])
assert len(result) == 1
assert result[0] == [intro, t]
def test_trailing_markdown_after_second_table() -> None:
t1, t2 = _table(), _table()
tail = _md("end")
result = split([t1, t2, tail])
assert len(result) == 2
assert result[1] == [t2, tail]
def test_non_table_elements_before_first_table_kept_in_first_group() -> None:
head = _md("head")
t1, t2 = _table(), _table()
result = split([head, t1, t2])
# head + t1 in group 0; t2 in group 1
assert result[0] == [head, t1]
assert result[1] == [t2]

View File

@@ -145,3 +145,78 @@ class TestMemoryConsolidationTypeHandling:
assert result is True
provider.chat.assert_not_called()
@pytest.mark.asyncio
async def test_list_arguments_extracts_first_dict(self, tmp_path: Path) -> None:
"""Some providers return arguments as a list - extract first element if it's a dict."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
# Simulate arguments being a list containing a dict
response = LLMResponse(
content=None,
tool_calls=[
ToolCallRequest(
id="call_1",
name="save_memory",
arguments=[{
"history_entry": "[2026-01-01] User discussed testing.",
"memory_update": "# Memory\nUser likes testing.",
}],
)
],
)
provider.chat = AsyncMock(return_value=response)
session = _make_session(message_count=60)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is True
assert "User discussed testing." in store.history_file.read_text()
assert "User likes testing." in store.memory_file.read_text()
@pytest.mark.asyncio
async def test_list_arguments_empty_list_returns_false(self, tmp_path: Path) -> None:
"""Empty list arguments should return False."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
response = LLMResponse(
content=None,
tool_calls=[
ToolCallRequest(
id="call_1",
name="save_memory",
arguments=[],
)
],
)
provider.chat = AsyncMock(return_value=response)
session = _make_session(message_count=60)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is False
@pytest.mark.asyncio
async def test_list_arguments_non_dict_content_returns_false(self, tmp_path: Path) -> None:
"""List with non-dict content should return False."""
store = MemoryStore(tmp_path)
provider = AsyncMock()
response = LLMResponse(
content=None,
tool_calls=[
ToolCallRequest(
id="call_1",
name="save_memory",
arguments=["string", "content"],
)
],
)
provider.chat = AsyncMock(return_value=response)
session = _make_session(message_count=60)
result = await store.consolidate(session, provider, "test-model", memory_window=50)
assert result is False